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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data sets (or cloud library) stored at Goddard.

Tao, Wei-Kuo↗
NASA NTRS2023

Comparative Accuracies of Models for Drag Prediction During Geomagnetically Disturbed Periods: A First Principles Model Versus Empirical Models

We examine the accuracy of density prediction by the first principles model Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) developed by the National Center for Atmospheric Research and compare it to the accuracy of three empirical models: Jacchia 71, the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Extended 2000 (NRLMSIS), Jacchia 1971, and Jacchia-Bowman 2008. Comparisons are made for three large storms: the October 2003 storm, the March 2013 storm, and the March 2015 storm. To evaluate the accuracy of these models we use tracking data for nine space objects in low Earth orbit. Additionally, we evaluate the accuracy of the TIEGCM and NRLMSIS with data from high precision accelerometers on the Challenging Minisatellite Payload (CHAMP) and Gravity field and Circulation Explorer (GOCE) satellites. The goal is to assess the use of a first principles model as a potential tool for forecasting satellite drag during large magnetic storms. For the storms considered, we found the TIEGCM, JB2008, and NRLMSIS models to be substantially more accurate than the Jacchia 71 model. The accuracies of the TIEGCM and JB2008 models were similar, but overall, the TIEGCM was more accurate. We found smaller differences for TIEGCM versus CHAMP than for NRLMIS for the Halloween Storm, and smaller differences than results published for JB2008 and the assimilative model HASDM. The empirical models are at present more practical for operational purposes, but the TIEGCM, developed as a research model, with a greater focus on operational use offers the potential for improved utility during stressing conditions.

R. L. Walterscheid↗
DOE OSTI2016

A stochastic wind turbine wake model based on new metrics for wake characterization

Abstract Understanding the detailed dynamics of wind turbine wakes is critical to predicting the performance and maximizing the efficiency of wind farms. This knowledge requires atmospheric data at a high spatial and temporal resolution, which are not easily obtained from direct measurements. Therefore, research is often based on numerical models, which vary in fidelity and computational cost. The simplest models produce axisymmetric wakes and are only valid beyond the near wake. Higher‐fidelity results can be obtained by solving the filtered Navier–Stokes equations at a resolution that is sufficient to resolve the relevant turbulence scales. This work addresses the gap between these two extremes by proposing a stochastic model that produces an unsteady asymmetric wake. The model is developed based on a large‐eddy simulation (LES) of an offshore wind farm. Because there are several ways of characterizing wakes, the first part of this work explores different approaches to defining global wake characteristics. From these, a model is developed that captures essential features of a LES‐generated wake at a small fraction of the cost. The synthetic wake successfully reproduces the mean characteristics of the original LES wake, including its area and stretching patterns, and statistics of the mean azimuthal radius. The mean and standard deviation of the wake width and height are also reproduced. This preliminary study focuses on reproducing the wake shape, while future work will incorporate velocity deficit and meandering, as well as different stability scenarios. Copyright © 2016 John Wiley & Sons, Ltd.

Doubrawa, Paula↗
DOE OSTI2022

A reduced model for the ITER divertor based on SOLPS solutions for ITER Q = 10 baseline conditions: B. A reduced model based on reversed-direction two point modeling

Edge codes such as SOLPS coupled to neutral codes such as EIRENE have become so comprehensive and sophisticated that they now constitute, in effect, 'code-experiments' that, as for actual experiments, can benefit from interpretation using simple models and conceptual frameworks, i.e. reduced models. The first task is the identification of options for the reduced model control parameters that are best suited for control of the action of the divertor, i.e. for control of target power loading and sputter–erosion, primarily. A strong correlation between the electron temperature at the divertor target, T e,t , and the neutral deuterium D 2 density at the target, n D2,t , flux-tube resolved, has recently been reported for a number of code studies including SOLPS-4.3 modeling of a set of ~50 ITER baseline cases: Q DT = 10, q 95 = 3, P SOL = 100 MW, metallic walls, and Ne seeding (Pitts et al 2019). Part A of the present study reports new results for largely the same ITER cases, confirming the strong correlation reported earlier between local values of T e,t , and (i) n D2,t , and (ii) normalized volumetric losses of power and pressure in the divertor. Strong correlations have now also been found, and are reported here for the first time, between T e,t and all of the divertor target quantities of practical interest. A physical explanation for this surprising result has not as yet been fully identified; nevertheless it has encouraging implications for reduced modeling of the ITER divertor. For such ITER conditions, (i) the global Ne injection rate, Inj Ne (Ne s –1 ), and (ii) the electron temperature at the location on the target where the peak power deposition occurs, T e,t @q ⊥,pk (eV), are found to be promising reduced model control parameters. In this part B, a reduced model for the ITER divertor is developed and described in detail, based on reversed-direction two point modeling, Rev2PM. The input to the reduced model is a value of the variable pair (T e,t @q ⊥,pk , Inj Ne )for a chosen case and the output are values of the various target as well as divertor-entrance quantities of practical interest, e.g. q ⊥,pk , the electron density at the X-point, n e,Xpt , etc. The reduced model was quantitatively characterized using one half of the code cases; it was then used to successfully predict (replicate) the code values of e.g. n e,Xpt for the other half.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Development and validation of chemistry agnostic flow battery cost performance model and application to nonaqueous electrolyte systems: Chemistry agnostic flow battery cost performance model

A chemistry agnostic cost performance model is described for a nonaqueous flow battery. The model predicts flow battery performance by estimating the active reaction zone thickness at each electrode as a function of current density, state of charge, and flow rate using measured data for electrode kinetics, electrolyte conductivity, and electrode-specific surface area. Validation of the model is conducted using a 4kW stack data at various current densities and flow rates. This model is used to estimate the performance of a nonaqueous flow battery with electrode and electrolyte properties used from the literature. The optimized cost for this system is estimated for various power and energy levels using component costs provided by vendors. The model allows optimization of design parameters such as electrode thickness, area, flow path design, and operating parameters such as power density, flow rate, and operating SOC range for various application duty cycles. A parametric analysis is done to identify components and electrode/electrolyte properties with the highest impact on system cost for various application durations. A pathway to 100$kWh -1 for the storage system is identified.

25 ENERGY STORAGE↗
DOE OSTI2016

Semiparametric modeling: Correcting low-dimensional model error in parametric models

In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consists of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Integrated optical and electrical modeling of plasmon-enhanced thin film photovoltaics: A case-study on organic devices

The nanoscale light control for absorption enhancement of organic photovoltaic (OPV) devices inevitably produces strongly non-uniform optical fields. These non-uniformities due to the localized optical modes are a primary route toward absorption enhancement in OPV devices. Therefore, a rigorous modeling tool taking into account the spatial distribution of optical field and carrier generation is necessary. Presented here is a comprehensive numerical model to describe the coupled optical and electrical behavior of plasmon-enhanced polymer:fullerene bulk heterojunction (BHJ) solar cells. In this model, a position-dependent electron-hole pair generation rate that could become highly non-uniform due to photonic nanostructures is directly calculated from the optical simulations. By considering the absorption and plasmonic properties of nanophotonic gratings included in two different popular device architectures, and applying the Poisson, current continuity, and drift/diffusion equations, the model predicts quantum efficiency, short-circuit current density, and desired carrier mobility ratios for bulk heterojunction devices incorporating nanostructures for light management. In particular, the model predicts a significant degradation of device performance when the carrier species with lower mobility are generated far from the collecting electrode. Consequently, an inverted device architecture is preferred for materials with low hole mobility. This is especially true for devices that include plasmonic nanostructures. Additionally, due to the incorporation of a plasmonic nanostructure, we use simulations to theoretically predict absorption band broadening of a BHJ into energies below the band gap, resulting in a 4.8% increase in generated photocurrent.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2020

GISS Model E2.2: A Climate Model Optimized for the Middle Atmosphere. Part 1: Model Structure, Climatology, Variability and Climate Sensitivity

We introduce a new climate model (GISS E2.2) that has been specially optimized for the Middle Atmosphere, and whose output is being contributed to the CMIP6 archive. The top of the model is at a geopotential altitude of 89 km, and parameterizations of moist convection and various forms of gravity wave drag based on tropospheric processes are chosen specifically for this optimization. We first evaluate the model in its configuration as a coupled atmosphere-chemistry model with respect to its simulation of the mean state of the Middle Atmosphere, from the mesosphere down through the Upper Troposphere/Lower Stratosphere. Then we assess its use as a coupled atmosphere-ocean climate model by exploring its mean ocean climatology. To evaluate its variability, we report on its simulation of the primary modes in the troposphere, stratosphere and ocean. Two climate change simulations are presented, the responses to instantaneous increases of 2xCO2 and 4xCO2, run with two different ocean models. Sensitivity studies are performed to illustrate the effect of parameterizations on the model results. We compare these results to the lower vertical resolution/top GISS Model E2.1, whose output has also been submitted to CMIP6. The different choices made for these models are explored. It is shown that important improvements in the circulation above and below the tropopause can be obtained when attention is paid to representation of Middle Atmosphere processes in climate model development.

D. Rind↗
DOE OSTI2017

Pairwise-interaction extended point-particle model for particle-laden flows

In this work we consider the pairwise interaction extended point-particle (PIEP) model for Euler–Lagrange simulations of particle-laden flows. By accounting for the precise location of neighbors the PIEP model goes beyond local particle volume fraction, and distinguishes the influence of upstream, downstream and laterally located neighbors. The two main ingredients of the PIEP model are (i) the undisturbed flow at any particle is evaluated as a superposition of the macroscale flow and a microscale flow that is approximated as a pairwise superposition of perturbation fields induced by each of the neighboring particles, and (ii) the forces and torque on the particle are then calculated from the undisturbed flow using the Faxén form of the force relation. The computational efficiency of the standard Euler–Lagrange approach is retained, since the microscale perturbation fields induced by a neighbor are pre-computed and stored as PIEP maps. Here we extend the PIEP force model of Akiki et al. with a corresponding torque model to systematically include the effect of perturbation fields induced by the neighbors in evaluating the net torque. Also, we use DNS results from a uniform flow over two stationary spheres to further improve the PIEP force and torque models. We then test the PIEP model in three different sedimentation problems and compare the results against corresponding DNS to assess the accuracy of the PIEP model and improvement over the standard point-particle approach. In the case of two sedimenting spheres in a quiescent ambient the PIEP model is shown to capture the drafting-kissing-tumbling process. In cases of 5 and 80 sedimenting spheres a good agreement is obtained between the PIEP simulation and the DNS. For all three simulations, the DEM-PIEP was able to recreate, to a good extent, the results from the DNS, while requiring only a negligible fraction of the numerical resources required by the fully-resolved DNS.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitation regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.

58 GEOSCIENCES↗
DOE OSTI2014

Modeling time-coincident ultrafast electron transfer and solvation processes at molecule-semiconductor interfaces

Kinetic models based on Fermi's Golden Rule are commonly employed to understand photoinduced electron transfer dynamics at molecule-semiconductor interfaces. Implicit in such second-order perturbative descriptions is the assumption that nuclear relaxation of the photoexcited electron donor is fast compared to electron injection into the semiconductor. This approximation breaks down in systems where electron transfer transitions occur on 100-fs time scale. Here, we present a fourth-order perturbative model that captures the interplay between time-coincident electron transfer and nuclear relaxation processes initiated by light absorption. The model consists of a fairly small number of parameters, which can be derived from standard spectroscopic measurements (e.g., linear absorbance, fluorescence) and/or first-principles electronic structure calculations. Insights provided by the model are illustrated for a two-level donor molecule coupled to both (i) a single acceptor level and (ii) a density of states (DOS) calculated for TiO{sub 2} using a first-principles electronic structure theory. These numerical calculations show that second-order kinetic theories fail to capture basic physical effects when the DOS exhibits narrow maxima near the energy of the molecular excited state. Overall, we conclude that the present fourth-order rate formula constitutes a rigorous and intuitive framework for understanding photoinduced electron transfer dynamics that occur on the 100-fs time scale.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Test Results of the CERN HL-LHC low- Quadrupole Short Models MQXFS3c and MQXFS4

For the High Luminosity Upgrade of the CERN Large Hadron Collider, lower * quadrupole magnets based on advanced Nb3Sn conductors will be installed on each side of the ATLAS and CMS experiment insertion zones. As part of the technological developments needed to achieve the required field gradient of 132.6 T/m within a 150-mm aperture, short length model magnets, named MQXFS, are tested both at the CERN SM18 and FERMI Lab test facilities. The model magnets rely on two types of Nb3Sn conductors (RRP and PIT) and on an innovative bladders and keys design to provide mechanical support against the Lorentz forces. In 2016 and 2017, the powering tests of the first two models MQXFS3 (RRP) and MQXFS5 (PIT) proved that nominal performance (16.5 kA) could be reached with excellent memory of the quench current after thermal cycle. However both magnets showed a slow training behavior with clear observations of voltage disturbances before the quench. Besides MQXFS5 only could reach ultimate current (17.9 kA) whereas erratic behavior was observed on MQXFS3 due to conductor local degradation at the head of one of the coil. In 2018, this limiting coil was changed and the applied azimuthal pre-stress increased. If ultimate current could then be reached, no stable current could be maintained due to identified defect on the outer layer of the new coil. Finally the outcome of the test of the new model MQXFS4, featuring the final RRP conductors that will be used for the series production and variation on the inner layer quench heater designs are here reported in details.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Model reduction for hypersonic aerodynamics via conservative LSPG projection and hyper-reduction

High-speed aerospace engineering applications rely heavily on computational fluid dynamics (CFD) models for design and analysis due to the expense and difficulty of flight tests and experiments. This reliance on CFD models necessitates performing accurate and reliable uncertainty quantification (UQ) of the CFD models. However, it is very computationally expensive to run CFD for hypersonic flows due to the fine grid resolution required to capture the strong shocks and large gradients that are typically present. Furthermore, UQ approaches are “many-query” problems requiring many runs with a wide range of input parameters. One way to enable computationally expensive models to be used in such many-query problems is to employ projection-based reduced-order models (ROMs) in lieu of the (high-fidelity) full-order model. In particular, the least-squares Petrov–Galerkin (LSPG) ROM (equipped with hyper-reduction) has demonstrated the ability to significantly reduce simulation costs while retaining high levels of accuracy on a range of problems including subsonic CFD applications. This allows computationally inexpensive LSPG ROM simulations to replace the full-order model simulations in UQ studies, which makes this many-query task tractable, even for large-scale CFD models. This work presents the first application of LSPG to a hypersonic CFD application. In particular, we present results for LSPG ROMs of the HIFiRE-1 in a three-dimensional, turbulent Mach 7.1 flow, showcasing the ability of the ROM to significantly reduce computational costs while maintaining high levels of accuracy in computed quantities of interest.

Fluid Dynamics↗
NASA NTRS1949

Longitudinal Stability and Control Characteristics of a Semispan Wind-Tunnel Model of the XF7U-1 Airplane and a Comparison with Complete-Model Wind-Tunnel Tests and Semispan-Model Wing-Flow Tests

An investigation was conducted on an 0.08-scale semispan model of the Chance Vought XF7U-1 airplane in the Langley high-speed 7- by 10-foot tunnel in the Mach number range from 0.40 to 0.97. The results are compared with those obtained with an 0.08-scale sting-mounted complete model tested in the same tunnel and with an 0.026-scale semispan model tested by the wing-flow method. The lift-curve slopes obtained for the 0.08-scale semispan model and the 0.026-scale wing-flow model were in good agreement but both were generally lower than the values obtained for the sting model. The results of an unpublished investigation have shown that tunnel-wall boundary-layer and strut-leakage effects can came the difference noted between the lift-curve slopes of the sting and the semispan data. Fair agreement was obtained among the data of the three models as regard the variation of pitching-moment coefficients with lift coefficient. The agreement between the complete and the semispan models was more favorable with the vertical fine on, because the wall-boundary-layer and strut leakage effects were less severe. In the Mach number range between 0.94 and 0.97, ailavator-control reversal was indicated in the wing-flow data near zero lift; Whereas, these same trends were indicated in the larger scale semispan data at somewhat higher lift coefficients.

Goodson, Kenneth W.↗
NASA NTRS2024

Modeling Atmospheric Brown Carbon in the GISS ModelE Earth System Model

Brown carbon (BrC) is an absorbing organic aerosol (OA), primarily emitted through biomass burning (BB), which exhibits light absorption unique to both black carbon (BC) and other organic aerosols. Despite many field and laboratory studies seeking to constrain BrC properties, the radiative forcing (RF) of BrC is still highly uncertain. To better understand its climate impact, we introduced BrC to the One-Moment Aerosol (OMA) module of the GISS ModelE Earth system model (ESM). We assessed ModelE sensitivity to primary BrC processed through a novel chemical aging scheme and to secondary BrC formed from biogenic volatile organic compounds (BVOCs). Initial results show that BrC typically contributes a top-of-the-atmosphere (TOA) radiative effect of 0.04 W m −2 . Sensitivity tests indicate that explicitly simulating BrC (separating it from other OAs), including secondary BrC, and simulating chemical bleaching of BrC contribute distinguishable radiative effects and should be accounted for in BrC schemes. This addition of prognostic BrC to ModelE allows greater physical and chemical complexity in OA representation with no apparent trade-off in model performance, as the evaluation of ModelE aerosol optical depth against Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) retrieval data, with and without the BrC scheme, reveals similar skill in both cases. Thus, BrC should be explicitly simulated to allow more physically based chemical composition, which is crucial for more detailed OA studies like comparisons to in situ measurement campaigns. We include a summary of best practices for BrC representation within ModelE at the end of this paper.

brown carbon aerosols↗